Geostatistical models often require a variogram or covariance model for kriging and krigingbased simulation. Next to the initial decision of stationarity, the choice of an appropriate variogram model is the most important decision in a geostatistical study. Common practice consists of fitting experimental variograms with a nested combination of proven models such as the spherical, exponential, ...

Geostatistical simulations are used to perform a global sensitivity analysis on a model Y = f(X1 ... Xk) where one of the model inputs Xi is a continuous 2D-field. Geostatistics allow specifying uncertainty on Xi with a spatial covariance model and generating random realizations of Xi. These random realizations are used to propagate uncertainty through model f and estimate global sensitivity in...

We propose a novel approach to landmark-based medical image registration based on the geostatical method of Kriging prediction. Our method exploits the spatial statistical relation between two images, as estimated using generalpurpose registration algorithms, in order to construct an optimum predictor of the displacement field. High accuracy is achieved by using an estimated spatial model of th...

Contents Summary 4 1 Motivation: time series normalization and adjustment 5 1.

Geostatistical modeling of petrophysical properties is a key step in modern integrated oil and gas reservoir studies. Recently, generative adversarial networks (GAN) have been shown to be a successful method for generating unconditional simulations of poreand reservoir-scale models. This contribution leverages the differentiable nature of neural networks to extend GANs to the conditional simula...

Transforming complex multivariate geological data to be multivariate Gaussian is an important and challenging problem in geostatistics. A variety of transforms are available to accomplish this goal, but may struggle with data sets of high dimensional and sample sizes. Projection Pursuit Density Estimation (PPDE) is a well-established non-parametric method for estimating the joint PDF of multiva...

of the many climatic events that influence the earth’s environment, drought is perhaps the one that is most linked with desertification. drought is the consequence of a natural reduction in the amount of precipitation received over an extended period, usually a season or more in length. drought monitoring is an essential component of drought risk management. it is normally performed using vario...

Abstract Cross-validation and performance measures are standard components in the evaluation of a geostatistical model. These well established univariate case, but for multivariate modeling have not received as much attention. In case single target variable, approaches remain valid, fully where vector variables needs to be estimated, based on all estimates simultaneously. An extension cross-val...

Environmental pollution of urban areas is one of key factors that state authorities and local agencies have to consider in the decisionmaking process. Understanding temporal and spatial distribution of air quality at the landscape scale is essential in assessing the potential ecological conditions for ecological restoration and in making decisions for regional management. To find a compromise a...